Efficient mobility metrics are necessary for mobile ad hoc networks to measure the impact of node mobility on performance. Normally, measuring mobility requires the use of complex localisation systems. A new mobility metric for performance measurements, the intra-vicinity dependency, is proposed. Its main novelty is that it can fully capture the relative motions between a node and its vicinity in a 2D plane, in real-time, using simple triangulation. Variants of this metric are proposed for predicting the performance of networks that follow group and random mobility models (e.g. inter-group inter-meeting times and packet delivery rate). To make the proposed mobility metrics more robust in noisy environments, a calibration method is also proposed for improving accuracy. Experimental results show that, without the help of any localisation systems, the proposed metrics enable a more accurate approximation of the average relative speed between mobile nodes/groups than existing methods. It is also shown that the proposed metrics yield excellent performance when they are used to predict the inter-group inter-meeting times for networks that follow the Rereence point group mobility model and to estimate the packet delivery rate for those that follow the Random Way Point model.